Industry
AIMS: All-Inclusive Multi-Level Segmentation for Anything
Despite the progress of image segmentation for accurate visual entity segmentation, completing the diverse requirements of image editing applications for differentlevel region-of-interest selections remains unsolved. In this paper, we propose a new task, All-Inclusive Multi-Level Segmentation (AIMS), which segments visual regions into three levels: part, entity, and relation (two entities with some semantic relationships). We also build a unified AIMS model through multi-dataset multi-task training to address the two major challenges of annotation inconsistency and task correlation. Specifically, we propose task complementarity, association, and prompt mask encoder for three-level predictions. Extensive experiments demonstrate the effectiveness and generalization capacity of our method compared to other state-of-the-art methods on a single dataset or the concurrent work on segment anything. We will make our code and training model publicly available.
Canadian premier wants to ban social media and AI chatbots for kids in Manitoba
The province's premier, Wab Kinew, proposed the ban during a fundraiser, but didn't elaborate on key details. Manitoba could be the first province in Canada to establish a social media ban for kids, but the proposal's details aren't very clear yet. The province's premier, Wab Kinew, announced during a fundraiser event on Saturday and on X that Manitoba would put in place a ban for social media and AI chatbots for its youth. They're doing these very awful things to kids all in the name of a few likes, all in the name of more engagement, and all in the name of money, Kinew said at the event. Our kids will never be for sale and their attention and their childhoods should never be profited from.
Do humanoids dream of becoming human?
Technology Robots Do humanoids dream of becoming human? Humanoids seem to be evolving into a distinct form. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. Stories of human-like dolls yearning to become real people turn up everywhere. Pinocchio wants to be a real boy. The robot child in Spielberg's wants to be loved like a human son.
Adversarial Teacher-Student Representation Learning for Domain Generalization
Domain generalization (DG) aims to transfer the learning task from a single or multiple source domains to unseen target domains. To extract and leverage the information which exhibits sufficient generalization ability, we propose a simple yet effective approach of Adversarial Teacher-Student Representation Learning, with the goal of deriving the domain generalizable representations via generating and exploring out-of-source data distributions. Our proposed framework advances Teacher-Student learning in an adversarial learning manner, which alternates between knowledge-distillation based representation learning and novel-domain data augmentation.